A Reference Architecture for Context-Aware Intelligent Traffic Management Platforms

A Reference Architecture for Context-Aware Intelligent Traffic Management Platforms

Zeenat Rehena (Aliah University, Kolkata, India), Marijn Janssen (Faculty of Technology, Policy and Management, Delft University of Technology, Delft, Netherlands) and Samiran Chattopadhyay (Department of Information Technology, Jadavpur University, Kolkata, India)
Copyright: © 2018 |Pages: 15
DOI: 10.4018/IJEGR.2018100105
OnDemand PDF Download:
List Price: $37.50
10% Discount:-$3.75


Smart cities have been heralded for improving traffic management by utilizing data for making better traffic management decisions. Multi-sided platforms collect data from sensors and citizen-generated data on one side and can provide input for decision-making using data analytics by governments and the public on the other side. However, there is no guidance for creating developing Intelligent Traffic Management Systems (ITMS) platforms. The involvement of various actors having different interest and heterogeneous datasets hampers development. In this article, the authors design a reference architecture (RA) to support intelligent traffic management systems for providing better a commute, and safety and security during travel based on real-time information. The main three layers of this RA are datasets, processes, and actors. The RA for ITMS provides guidance for designing and overcoming the challenges with: 1) heterogeneous datasets; 2) data gathering; 3) data processing; 4) data management; and 5) supporting various types of data users. The illustration and evaluation of the architecture shows possible solutions of the aforementioned challenges. The RA helps to integrate the activities performed by the various actors. In this way it can be used to reduce traffic queues, increase the efficient use of resources, smooth and safe commute of the citizens.
Article Preview

1. Introduction

The increasing level of urbanization and growth in size and number of cities in different parts of the world has resulted in both challenges and opportunities. New ways for city planning are needed (Axelsson & Granath, 2018). Many governments at different levels – regional, national, international, have initiated programs on digital and smart cities (Anthopoulos, 2017). The initiatives contribute to national and international health, economy, infrastructure, resources and transportation to provide high quality of comfort to their citizens. Smart city has become one of the most promising, prominent and challenging application in the area of Wireless Sensor Networks (WSNs), Internet of Things (IoTs) and Big Data analytics, but has been criticized for not being able to hold if promises (Anthopoulos, Janssen & Weerakkody, 2016). Smart Cities employ information and communication technology (ICT) to improve city operations and services and connect to citizens. IoT can be used to collect high quality data (Chatterjee, Kar & Gupta, 2018) and big data analytics can make sense of the data (Chong, Habib, Evangelopoulos & Park, 2018). Anthopoulos & Reddick (2016), it is found that six dimensions: people, government, economy, mobility, environment and living enhancing the urban life style. Smart cities can play a significant role to deal with these urban challenges. Lee and Lee (2014) provides a typology of different kinds of smart services ranging from automation to transformative. Today’s cities are shifting and transforming into test beds where solutions driven by information and communication technologies (ICT) impact people interactions and vice versa (Gottschalk et al., 2016). Among various application areas of smart cities like smart water, energy, buildings, health, intelligent traffic management system (ITMS) can have significant impact on day to day life of the citizen (Anthopoulos & Reddick, 2016).

The limited capacity and uneven use of the existing transportation infrastructure can lead to the severe traffic congestion and in increasing travel times. The problems of road traffic can be resolved by either improving the existing road infrastructure or by using ITMS to improve the usage of existing infrastructure. The latter might require less investment and at the same time can reduce pollution and energy consumption and improve travelling time and convenience. For example in (http://urbact.eu/steering-real-time-city-through-urban-big-data-and-city-dashboards-0) and (Amaral et al., 2016) the smart city of Rio de Janeiro draws together real-time data streams from thirty agencies and try to manage a large, complex city. The dashboards are used by the city managers and analyst to monitor the system or the city how it works as a whole.

In addition to the economic advantages, one of the most critical consequences of traffic congestion impact the operation of emergency services, such as medical, fire, rescue operations and police services etc. These services demand efficient and timely response of emergency vehicles. Further, in parallel to the growth of population existing road sizes are not expanded in the same proportion. As a result, vehicle crashes are more often happened in the narrow, congested roads as the drivers or the travellers want to go fast to avoid congestion on road. In turn, it affects the social aspects of the city life. Finally, due to the modern city life-style demands shorten commuter journey, reliable and accurate traffic prediction, early detection of bottlenecks on road, parking management becomes more important.

Complete Article List

Search this Journal:
Volume 19: 1 Issue (2023): Forthcoming, Available for Pre-Order
Volume 18: 4 Issues (2022): 2 Released, 2 Forthcoming
Volume 17: 4 Issues (2021)
Volume 16: 4 Issues (2020)
Volume 15: 4 Issues (2019)
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing